Objective: To discuss strategies and methods of normalization on how to deal with and analyze data for different chips with the combination of statistics, mathematics and bioinformatics in order to find significant difference genes. Methods: With Excel and SPSS software, high or low density chips were analyzed through total intensity normalization (TIN) and locally weighted linear regression normalization (LWLRN). Results: These methods effectively reduced systemic errors and made data more comparable and reliable. Conclusion: These methods can search the genes of significant difference, although normalization methods are being developed and need to be improved further. Great breakthrough will be obtained in microarray data normalization analysis and transformation with the development of non-linear technology, software and hardware of computer.